Software Engineer, AI Security
Job Description: • Design, implement, test and release e2e workflows for our AI security product. • Work across multiple agent platforms like AWS Bedrock, Google AgentSpace, Salesforce AgentForce, building foundational solutions, using cloud, SAAS and AI design patterns and technologies. • Use AI and Agents to secure AI, using CUA agents, various LLM’s, agentic frameworks like ADK, Langchain among others. • Design and develop secure, scalable, multi-tenant software solutions that run seamlessly across major cloud platforms like AWS and Azure. • Act as a technical expert and thought leader, influencing product direction and engineering best practices. • Drive continuous improvement in engineering processes, tooling, and operational reliability. • Collaborate with internal teams to produce software design and architecture • Test and deploy applications and systems. • Revise, update, refactor and debug code. • Ability to start a program from scratch as well as maintain existing services. • Develop documentation throughout the software development life cycle. • Serve as an expert on applications and provide technical support. Requirements: • 10+ years of software engineering experience • Expert-level ability utilizing technologies such as Java, Spring Framework, REST and Microservices • Familiar with AI tools and curious about MCP, A2A, Agentic frameworks. Have a continuous learning mindset and not hesitate to venture into unchartered territory • Ability to perform research and go deep into platforms is a strong plus • Strong Experience as a Java Engineer developing applications based on Security principles, cloud platforms (AWS, Azure, or Google Cloud) and Containerization (Docker, Kubernetes) • Deep understanding of data structures, algorithms, and design patterns • Hands on experience with SQL, ElasticSearch, Redis, CI/CD, AWS Glue, Kafka • Experience in increasing levels of responsibility managing application development, solution architecture, design and delivery, and process improvement • Experience with unit, functional and system integration testing • Extensive understanding of working in an agile environment utilizing Scrum and Kanban • Experience with Git (GitHub/GitLab), automatic deployments, continuous integration • Hands on experience using IntelliJ or Eclipse/My Eclipse IDE, writing Junit test cases, working with Maven/Ant • Experience with AI development tools in SDLC such as Amazon Q, Github Copilot, Cursor, and similar productivity assistants • Familiarity with various architectural patterns (e.g., event-driven, microservices, serverless) and their trade-offs Benefits: Apply tot his job